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1. Neutrino oscillation constraints on U(1)′ models: from non-standard interactions to long-range forces

   https://doi.org/10.1007/JHEP01(2021)114  

   Coloma, Pilar ; Gonzalez-Garcia, M. C. ; Maltoni, Michele ( January 2021 , Journal of High Energy Physics)

   null (Ed.)

   A bstract We quantify the effect of gauge bosons from a weakly coupled lepton flavor dependent U(1) ′ interaction on the matter background in the evolution of solar, atmospheric, reactor and long-baseline accelerator neutrinos in the global analysis of oscillation data. The analysis is performed for interaction lengths ranging from the Sun-Earth distance to effective contact neutrino interactions. We survey ∼ 10000 set of models characterized by the six relevant fermion U(1) ′ charges and find that in all cases, constraints on the coupling and mass of the Z′ can be derived. We also find that about 5% of the U(1) ′ model charges lead to a viable LMA-D solution but this is only possible in the contact interaction limit. We explicitly quantify the constraints for a variety of models including $$ \mathrm{U}{(1)}_{B-3{L}_e} $$ U 1 B − 3 L e , $$ \mathrm{U}{(1)}_{B-3{L}_{\mu }} $$ U 1 B − 3 L μ , $$ \mathrm{U}{(1)}_{B-3{L}_{\tau }} $$ U 1 B − 3 L τ , $$ \mathrm{U}{(1)}_{B-\frac{3}{2}\left({L}_{\mu }+{L}_{\tau}\right)} $$ U 1 B − 3 2 L μ + L τ , $$ \mathrm{U}{(1)}_{L_e-{L}_{\mu }} $$ U 1 L e − L μ , $$ \mathrm{U}{(1)}_{L_e-{L}_{\tau }} $$ U 1 L e − L τ , $$ \mathrm{U}{(1)}_{L_e-\frac{1}{2}\left({L}_{\mu }+{L}_{\tau}\right)} $$ U 1 L e − 1 2 L μ + L τ . We compare the constraints imposed by our oscillation analysis with the strongest bounds from fifth force searches, violation of equivalence principle as well as bounds from scattering experiments and white dwarf cooling. Our results show that generically, the oscillation analysis improves over the existing bounds from gravity tests for Z′ lighter than ∼ 10 − 8 → 10 − 11 eV depending on the specific couplings. In the contact interaction limit, we find that for most models listed above there are values of g′ and M Z′ for which the oscillation analysis provides constraints beyond those imposed by laboratory experiments. Finally we illustrate the range of Z′ and couplings leading to a viable LMA-D solution for two sets of models. 

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2. Can machine learning reveal precursors of reversals of the geomagnetic axial dipole field?

   https://doi.org/10.1093/gji/ggac195  

   Gwirtz, K. ; Davis, T. ; Morzfeld, M. ; Constable, C. ; Fournier, A. ; Hulot, G. ( May 2022 , Geophysical Journal International)

   It is well known that the axial dipole part of Earth’s magnetic field reverses polarity, so that the magnetic North Pole becomes the South Pole and vice versa. The timing of reversals is well documented for the past 160 Myr, but the conditions that lead to a reversal are still not well understood. It is not known if there are reliable ‘precursors’ of reversals (events that indicate that a reversal is upcoming) or what they might be. We investigate if machine learning (ML) techniques can reliably identify precursors of reversals based on time-series of the axial magnetic dipole field. The basic idea is to train a classifier using segments of time-series of the axial magnetic dipole. This training step requires modification of standard ML techniques to account for the fact that we are interested in rare events—a reversal is unusual, while a non-reversing field is the norm. Without our tweak, the ML classifiers lead to useless predictions. Perhaps even more importantly, the usable observational record is limited to 0–2 Ma and contains only five reversals, necessitating that we determine if the data are even sufficient to reliably train and validate an ML algorithm. To answer these questions we use several ML classifiers (linear/non-linear support vector machines and long short-term memory networks), invoke a hierarchy of numerical models (from simplified models to 3-D geodynamo simulations), and two palaeomagnetic reconstructions (PADM2M and Sint-2000). The performance of the ML classifiers varies across the models and the observational record and we provide evidence that this is not an artefact of the numerics, but rather reflects how ‘predictable’ a model or observational record is. Studying models of Earth’s magnetic field via ML classifiers thus can help with identifying shortcomings or advantages of the various models. For Earth’s magnetic field, we conclude that the ability of ML to identify precursors of reversals is limited, largely due to the small amount and low frequency resolution of data, which makes training and subsequent validation nearly impossible. Put simply: the ML techniques we tried are not currently capable of reliably identifying an axial dipole moment (ADM) precursor for geomagnetic reversals. This does not necessarily imply that such a precursor does not exist, and improvements in temporal resolution and length of ADM records may well offer better prospects in the future.

    

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3. Allosteric communication in the gating mechanism for controlled protein degradation by the bacterial ClpP peptidase

   https://doi.org/10.1063/5.0139184  

   Dayananda, Ashan ; Dennison, T. S. ; Fonseka, Hewafonsekage Yasan ; Avestan, Mohammad S. ; Wang, Qi ; Tehver, Riina ; Stan, George ( March 2023 , The Journal of Chemical Physics)

   Proteolysis is essential for the control of metabolic pathways and the cell cycle. Bacterial caseinolytic proteases (Clp) use peptidase components, such as ClpP, to degrade defective substrate proteins and to regulate cellular levels of stress-response proteins. To ensure selective degradation, access to the proteolytic chamber of the double–ring ClpP tetradecamer is controlled by a critical gating mechanism of the two axial pores. The binding of conserved loops of the Clp ATPase component of the protease or small molecules, such as acyldepsipeptide (ADEP), at peripheral ClpP ring sites, triggers axial pore opening through dramatic conformational transitions of flexible N-terminal loops between disordered conformations in the “closed” pore state and ordered hairpins in the “open” pore state. In this study, we probe the allosteric communication underlying these conformational changes by comparing residue–residue couplings in molecular dynamics simulations of each configuration. Both principal component and normal mode analyses highlight large-scale conformational changes in the N-terminal loop regions and smaller amplitude motions of the peptidase core. Community network analysis reveals a switch between intra- and inter-protomer coupling in the open–closed pore transition. Allosteric pathways that connect the ADEP binding sites to N-terminal loops are rewired in this transition, with shorter network paths in the open pore configuration supporting stronger intra- and inter-ring coupling. Structural perturbations, either through the removal of ADEP molecules or point mutations, alter the allosteric network to weaken the coupling. 

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4. Spatiokinematic models of five nova remnants: correlations between nova shell axial ratio, expansion velocity, and speed class

   https://doi.org/10.1093/mnras/stac563  

   Santamaría, E. ; Guerrero, M. A. ; Zavala, S. ; Ramos-Larios, G. ; Toalá, J. A. ; Sabin, L. ( March 2022 , Monthly Notices of the Royal Astronomical Society)

   We present long-slit intermediate-dispersion spectroscopic observations and narrow-band direct imaging of four classical nova shells, namely T Aur, HR Del, DQ Her, and QU Vul, and the nova-like source CK Vul. These are used to construct models of their nebular remnants using the morphokinematic modelling tool shape to reveal their 3D shape. All these nova remnants but CK Vul can be described by prolate ellipsoidal shells with different eccentricity degree, from the spherical QU Vul to the highly elongated shell with an equatorial component HR Del. On the other hand, CK Vul shows a more complex structure, with two pairs of nested bipolar lobes. The spatiokinematic properties of the ellipsoidal nova shells derived from our models include their true axial ratios. This parameter is expected to correlate with the expansion velocity and decline time t3 (i.e. their speed class) of a nova as the result the interaction of the ejecta with the circumstellar material and rotation speed and magnetic field of the white dwarf. We have compared these three parameters including data available in the literature for another two nova shells, V533 Her and FH Ser. There is an anticorrelation between the expansion velocity and the axial ratio and decline time t3 for nova remnants with ellipsoidal morphology, and a correlation between their axial ratios and decline times t3, confirming theoretical expectations that the fastest expanding novae have the smallest axial ratios. We note that the high expansion velocity of the nova shell HR Del of 615 km s−1 is inconsistent with its long decline time t3 of 250 d.

    

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5. Hyperelastic continuum models for isotropic athermal fibrous networks

   https://doi.org/10.1098/rsfs.2022.0043  

   Song, Dawei ; Oberai, Assad A. ; Janmey, Paul A. ( December 2022 , Interface Focus)

   Many biological materials contain fibrous protein networks as their main structural components. Understanding the mechanical properties of such networks is important for creating biomimicking materials for cell and tissue engineering, and for developing novel tools for detecting and diagnosing disease. In this work, we develop continuum models for isotropic, athermal fibrous networks by combining a single-fibre model that describes the axial response of individual fibres, with network models that assemble individual fibre properties into overall network behaviour. In particular, we consider four different network models, including the affine, three-chain, eight-chain, and micro-sphere models, which employ different assumptions about network structure and kinematics. We systematically investigate the ability of these models to describe the mechanical response of athermal collagen and fibrin networks by comparing model predictions with experimental data. We test how each model captures network behaviour under three different loading conditions: uniaxial tension, simple shear, and combined tension and shear. We find that the affine and three-chain models can accurately describe both the axial and shear behaviour, whereas the eight-chain and micro-sphere models fail to capture the shear response, leading to unphysical zero shear moduli at infinitesimal strains. Our study is the first to systematically investigate the applicability of popular network models for describing the macroscopic behaviour of athermal fibrous networks, offering insights for selecting efficient models that can be used for large-scale, finite-element simulations of athermal networks. 

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